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Today, I'd like to show you how we use the FlexiLayout Studio and our FlexiLayout out templates to extract tables or tabular information from documents. Now I'm going to show you my samples real quick. I have a document that has two pages worth of tables. We have a part number, a description or a name, and then we have a price and it's two pages. It's two pages long. And then my last sample here is another table where we have a name or description and we have a price, but we don't have a part number. And so we want to extract this information from the documents. And make sure that we process them accordingly. So what I'm going to do, and this is probably one of the most important first steps that we can do, is we need to add a block. And this is going to be a table block. And what we'll do here is we'll create our columns. So I did share with you, we have a part number, we have a name, it's a name or a description, and then we have a price. Okay, so we're simply going to define our fields here and just to keep this video a little bit speedier, we've already assumed that we know the headers or how a document starts in our case, but let's go ahead and add a table element. Now when we add a table element, we can of course give it an intelligent name and we can tell the software here about the columns. But if you realize it's actually looking for a block, that's the block that we created in the first step. So we're just simply gonna go tell the software about that block. Now of course we'd want to name this something intelligent, like a table block, or something similar to that. So you can see here we have part number, name and description, and a price.

If you look at the properties of these, you can see we can get very, very specific. Now for ease of our first table, we're going to keep it very simple and we'll just simply use keywords as part of the name. But you can see, we can reference other elements of a document to tell us when a table starts honestly and when it even stops. So a lot of different configuration we can take here. I won't do it for ease of this demo, but obviously super flexibility here when we're extracting tables for this demo, I know that the word description is sometimes found or the word name is sometimes found, so I'm just simply going to tell the software. This can be name or description by using our pipe symbol there.

We have other columns that are pretty relevant to us. If there's a fixed column order, we want to tell the software that, and I'll just double click here so you kind of see what we do, but it's really just defining your own order. You can have an array of these, so if you have multiple different ways, a document table comes in, you can of course set multiple different column orders for that. Here we'll tell the software to use a header and we can even tell the software to look for a footer that is optional by default and we can tell the software how to detect rows. Now you can understand for this demo that I'm keeping it very simple and these are very simple tables, but I want you to understand the amount of flexibility you have here. As you just looked at those three tabs, there's a lot of different options that we can use using source elements and other search elements that we have to get our tables zoned in here for us.

So once again, I have our columns here applied. I'm just going to go ahead and set these up to be processed. I'm just going to right click on our first item here and match. And what I'll show you here is that we were able to extract the table. Now you can of course double click on the table and see some more of the specifics here. And you can see we've got our part number column, our name slash description column and our price column. And then here on my other sample, I will go ahead and match this one as well. And by clicking on the table element, I once again have the name, description, and the price and realized how in my demo here I don't have a part number field. And there's configuration of course that can either let that be optional or force it to be required.

But this is pretty awesome in how we extract a table. It's very easy and it's very flexible in the way we do it; a lot of different ways that we can configure it to do what we want it to do. But once I've extracted the table here, just as our usual practice, we can export this to our AFL file and then upload that to a project. And now we're processing tables accordingly. I hope you enjoyed this video. Please let me know if you have any questions and thank you so much!

Articles by Travis Spangler: Travis writes articles dealing with various technical aspects of document capture and forms processing. He is fluent in Microsoft.NET and holds several certifications including ABBYY FlexiCapture and IRISXTract.
As general manager and sales director, he controls the daily operations as well as manages customer accounts to ensure both customers and prospects are receiving the very best from UFC, Inc.
Travis has many years of experience with document capture software and content management systems. He also has wide areas of expertise including custom functions in ABBYY FlexiCapture, email API's, Microsoft SQL Server Reporting Services, and many other applications and platforms. He has integrated Amazon Web Services EC2 instances with several applications including the company's CRM system.

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